Image matching is a technique being used in computer vision, object recognition, motion tracking, three-dimensional (3D) modeling, and the like, which can be performed to check whether two images contain the same content. For example, a user interested in determining availability of a book can capture an image of the book and submit that image to an image matching service as a query image in order to be provided with information associated with the book in return. In order to accomplish this, features of the query image can be transformed into feature descriptors and compared to feature descriptors of images of books, in this example, stored with the image matching service. Once a corresponding match is identified, information associated with the matching image (e.g., information for purchasing the book) can be provided and displayed to the user on their computing device. Accordingly, as object recognition, motion tracking, 3D modeling, and like become more widely used and as products and services provided by image matching searches increase, the amount of images being stored in various databases to enable the same are increasing. Since space for storing these images (or their respective feature descriptors) is often limited and/or expensive, it can be advantageous to adapt not only the way in which these images are stored for recall and comparison, but also the way their associated storage systems are scaled.